docstr: Tests that all supported dtypes work without error.
docstr_tok: ["Tests","that","all","supported","dtypes","work","without","error","."]
code: def test_dtypes_works_correctly(self):
      """Tests that all supported dtypes work without error."""
      dim = 3
      sample_float32 = (
          sample_halton_sequence_lib.sample_halton_sequence(
              dim,
              num_results=10,
              dtype=tf.float32,
              seed=test_util.test_seed(),
          )
      )
      sample_float64 = (
          sample_halton_sequence_lib.sample_halton_sequence(
              dim,
              num_results=10,
              dtype=tf.float64,
              seed=test_util.test_seed(),
          )
      )
      self.assertEqual(self.evaluate(sample_float32).dtype, np.float32)
      self.assertEqual(self.evaluate(sample_float64).dtype, np.float64)
  
file_path: probability/tensorflow_probability/python/mcmc/sample_halton_sequence_test.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import monte_carlo
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import sample_halton_sequence_lib
label_desc: Use image node_id 4 for calling the HaltonSequenceTest obj's underlying member method code with example usage: obj.test_dtypes_works_correctly() without return types